package com.atguigu.day09;

import com.atguigu.bean.WaterSensor;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.annotation.DataTypeHint;
import org.apache.flink.table.annotation.FunctionHint;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.functions.AggregateFunction;
import org.apache.flink.table.functions.TableFunction;
import org.apache.flink.types.Row;
import org.apache.hadoop.yarn.webapp.hamlet2.Hamlet;

import static org.apache.flink.table.api.Expressions.$;
import static org.apache.flink.table.api.Expressions.call;

public class Flink03_UDF_AggFun {
    public static void main(String[] args) {
        //1获取流的执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        env.setParallelism(1);

        //2.从端口读取数据
        SingleOutputStreamOperator<WaterSensor> streamOperator = env.socketTextStream("localhost", 9999)
                .map(new MapFunction<String, WaterSensor>() {
                    @Override
                    public WaterSensor map(String value) throws Exception {
                        String[] split = value.split(",");
                        return new WaterSensor(split[0], Long.parseLong(split[1]), Integer.parseInt(split[2]));
                    }
                });


        //3.获取表的执行环境
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

        //4.将流转为表
        Table table = tableEnv.fromDataStream(streamOperator);

        /*table
                .groupBy($("id"))
                .select($("id"),call(MyUDAF.class,$("vc")))
                .execute()
                .print();*/

//        TODO 注册一个自定义函数
        tableEnv.createTemporarySystemFunction("vcAvg", MyUDAF.class);

/* table
                .groupBy($("id"))
                .select($("id"),call("vcAvg",$("vc")))
                .execute()
                .print();*/

        tableEnv.executeSql("select id,vcAvg(vc) from "+table+" group by id").print();
    }

    public static class MyAvgAcc {
        public Integer sum;
        public Integer count;
    }

    //自定义一个聚合函数（多进一出） 根据id求vc的平均值
    public static class MyUDAF extends AggregateFunction<Double, MyAvgAcc> {

        @Override
        public MyAvgAcc createAccumulator() {
            MyAvgAcc myAvgAcc = new MyAvgAcc();
            myAvgAcc.sum = 0;
            myAvgAcc.count = 0;
            return myAvgAcc;
        }


        public void accumulate(MyAvgAcc acc, Integer value) {
            acc.sum += value;
            acc.count += 1;
        }


        @Override
        public Double getValue(MyAvgAcc accumulator) {
            if (accumulator.count == 0) {

                return null;
            } else {
                return accumulator.sum * 1D / accumulator.count;
            }
        }
    }
}
